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CCIBA*: An Improved BA* Based Collaborative Coverage Path Planning Method for Multiple Unmanned Surface Mapping Vehicles
Hubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan 430063, China, also with the Sanya Science and Education Innovation Park, Wuhan University of Technology, Sanya 572000, China, and also with the Chongqing Research Institute, Wuhan University of Technology, Chongqing 401120, China..ORCID iD: 0000-0003-0418-9210
Hubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan 430063, China, also with the Sanya Science and Education Innovation Park, Wuhan University of Technology, Sanya 572000, China, and also with the Chongqing Research Institute, Wuhan University of Technology, Chongqing 401120, China..
Faculty of Mechanical Engineering, Opole University of Technology, 45758 Opole, Poland, and also with the Yonsei Frontier Laboratory, Yonsei University, Seodaemun-gu, Seoul 03722, Republic of Korea.ORCID iD: 0000-0003-4067-0669
Hubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan 430063, China, also with the Sanya Science and Education Innovation Park, Wuhan University of Technology, Sanya 572000, China, and also with the Chongqing Research Institute, Wuhan University of Technology, Chongqing 401120, China..
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2022 (English)In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 23, no 10, p. 19578-19588Article in journal (Refereed) Published
Abstract [en]

The main emphasis of this work is placed on the problem of collaborative coverage path planning for unmanned surface mapping vehicles (USMVs). As a result, the collaborative coverage improved BA* algorithm (CCIBA*) is proposed. In the algorithm, coverage path planning for a single vehicle is achieved by task decomposition and level map updating. Then a multiple USMV collaborative behavior strategy is designed, which is composed of area division, recall and transfer, area exchange and recognizing obstacles. Moverover, multiple USMV collaborative coverage path planning can be achieved. Consequently, a high-efficiency and high-quality coverage path for USMVs can be implemented. Water area simulation results indicate that our CCIBA* brings about a substantial increase in the performances of path length, number of turning, number of units and coverage rate.

Place, publisher, year, edition, pages
IEEE, 2022. Vol. 23, no 10, p. 19578-19588
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:mau:diva-51517DOI: 10.1109/tits.2022.3170322ISI: 000801210300001Scopus ID: 2-s2.0-85132513213OAI: oai:DiVA.org:mau-51517DiVA, id: diva2:1658978
Available from: 2022-05-18 Created: 2022-05-18 Last updated: 2024-02-05Bibliographically approved

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Malekian, Reza

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Ma, YongLi, ZhixiongMalekian, RezaSotelo, Miguel Angel
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Department of Computer Science and Media Technology (DVMT)Internet of Things and People (IOTAP)
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Control Engineering

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